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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha : |
21/02/2014 |
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Actualizado : |
28/06/2018 |
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Tipo de producción científica : |
Documentos |
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Autor : |
VIÑOLES, C.; CUADRO, P.; SOARES DE LIMA, J.M.; DE BARBIERI, I.; CUADRO, R.; MOREIRA, L.; RODRÍGUEZ, H.; FERREIRA, E.; CAZZULI, F.; LEVRATTO, J.; FRUGONI, J.C.; MONTOSSI, F. |
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Afiliación : |
CAROLINA VIÑOLES GIL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PABLO ANDRES CUADRO BRAS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN MANUEL SOARES DE LIMA LAPETINA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WASHINGTON ROBIN CUADRO LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS EDUARDO MOREIRA SANTANA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; EDGAR DANIEL FERREIRA FABILA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FIORELLA CARLA CAZZULI ALBA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN CARLOS LEVRATTO CORTES, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JULIO CESAR FRUGONI SILVEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
El entore precoz como alternativa para aumentar la competitividad de la cría. |
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Fecha de publicación : |
2012 |
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Fuente / Imprenta : |
ln: INIA Tacuarembó. Unidad Experimental Glencoe. Día de Campo Unidad Experimental Glencoe [Colonia Fernando Baccaro, Guarapirú, Paysandú], 2012. Propuestas tecnológicas para sistemas ganaderos de Basalto. Tacuarembó (Uruguay): INIA, 2012. |
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Páginas : |
p. 4-8 |
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Serie : |
(INIA Serie Actividades de Difusión ; 693) |
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Idioma : |
Español |
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Contenido : |
En Uruguay, la cría se lleva a cabo en los suelos de menor productividad, fenómeno que se ha visto acentuado en los últimos 10 años, producto de la competencia con otros rubros como la agricultura y la forestación. Esta situación, asociada a otros factores de mercado y aspectos socioeconómicos, redunda en una baja eficiencia reproductiva de los sistemas de cría, reflejada por bajos porcentajes promedio de destete (64%), entre otros indicadores. Estas bajas tasas de procreo, determinadas por largos períodos de anestro posparto (>120 días en vacas de primera cría) y una elevada edad al primer entore (53% se entoran con más de 2 años de edad), limitan la
producción de carne lograda por hectárea por los sistemas criadores o de ciclo completo e intermedios. Además del reducido número de terneros logrados, los bajos pesos al destete (140-160 kg) limitan aún más la productividad de la cría. Una alternativa para aumentar la competitividad del rubro es reducir la edad al primer entore, con abundante información tecnológica generada por INIA para disminuirla de 3 a 2 años. Sin embargo, los estudios de investigación para reducir la edad de entore a 14 meses son escasos. El beneficio de esta alternativa radica en eliminar una categoría improductiva del rodeo e incrementar consecuentemente, el número de vacas en producción. Si bien el equipo de INIA ha demostrado que esta alternativa aumenta la productividad y el ingreso de los sistemas criadores, la misma requiere necesariamente de una intensificación importante de la recría de las terneras. MenosEn Uruguay, la cría se lleva a cabo en los suelos de menor productividad, fenómeno que se ha visto acentuado en los últimos 10 años, producto de la competencia con otros rubros como la agricultura y la forestación. Esta situación, asociada a otros factores de mercado y aspectos socioeconómicos, redunda en una baja eficiencia reproductiva de los sistemas de cría, reflejada por bajos porcentajes promedio de destete (64%), entre otros indicadores. Estas bajas tasas de procreo, determinadas por largos períodos de anestro posparto (>120 días en vacas de primera cría) y una elevada edad al primer entore (53% se entoran con más de 2 años de edad), limitan la
producción de carne lograda por hectárea por los sistemas criadores o de ciclo completo e intermedios. Además del reducido número de terneros logrados, los bajos pesos al destete (140-160 kg) limitan aún más la productividad de la cría. Una alternativa para aumentar la competitividad del rubro es reducir la edad al primer entore, con abundante información tecnológica generada por INIA para disminuirla de 3 a 2 años. Sin embargo, los estudios de investigación para reducir la edad de entore a 14 meses son escasos. El beneficio de esta alternativa radica en eliminar una categoría improductiva del rodeo e incrementar consecuentemente, el número de vacas en producción. Si bien el equipo de INIA ha demostrado que esta alternativa aumenta la productividad y el ingreso de los sistemas criadores, la misma requiere necesariamente de una ... Presentar Todo |
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Palabras claves : |
ANIMAL PRODUCTION; ENTORE; ENTORE A LOS 14 MESES DE EDAD; ENTORE PRECOZ; PESO AL DESTETE; RECRIA. |
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Thesagro : |
GANADERIA. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/10579/1/SAD-693p4-8.pdf
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Marc : |
LEADER 02754naa a2200361 a 4500
001 1026194
005 2018-06-28
008 2012 bl uuuu u00u1 u #d
100 1 $aVIÑOLES, C.
245 $aEl entore precoz como alternativa para aumentar la competitividad de la cría.
260 $c2012
300 $ap. 4-8
490 $a(INIA Serie Actividades de Difusión ; 693)
520 $aEn Uruguay, la cría se lleva a cabo en los suelos de menor productividad, fenómeno que se ha visto acentuado en los últimos 10 años, producto de la competencia con otros rubros como la agricultura y la forestación. Esta situación, asociada a otros factores de mercado y aspectos socioeconómicos, redunda en una baja eficiencia reproductiva de los sistemas de cría, reflejada por bajos porcentajes promedio de destete (64%), entre otros indicadores. Estas bajas tasas de procreo, determinadas por largos períodos de anestro posparto (>120 días en vacas de primera cría) y una elevada edad al primer entore (53% se entoran con más de 2 años de edad), limitan la producción de carne lograda por hectárea por los sistemas criadores o de ciclo completo e intermedios. Además del reducido número de terneros logrados, los bajos pesos al destete (140-160 kg) limitan aún más la productividad de la cría. Una alternativa para aumentar la competitividad del rubro es reducir la edad al primer entore, con abundante información tecnológica generada por INIA para disminuirla de 3 a 2 años. Sin embargo, los estudios de investigación para reducir la edad de entore a 14 meses son escasos. El beneficio de esta alternativa radica en eliminar una categoría improductiva del rodeo e incrementar consecuentemente, el número de vacas en producción. Si bien el equipo de INIA ha demostrado que esta alternativa aumenta la productividad y el ingreso de los sistemas criadores, la misma requiere necesariamente de una intensificación importante de la recría de las terneras.
650 $aGANADERIA
653 $aANIMAL PRODUCTION
653 $aENTORE
653 $aENTORE A LOS 14 MESES DE EDAD
653 $aENTORE PRECOZ
653 $aPESO AL DESTETE
653 $aRECRIA
700 1 $aCUADRO, P.
700 1 $aSOARES DE LIMA, J.M.
700 1 $aDE BARBIERI, I.
700 1 $aCUADRO, R.
700 1 $aMOREIRA, L.
700 1 $aRODRÍGUEZ, H.
700 1 $aFERREIRA, E.
700 1 $aCAZZULI, F.
700 1 $aLEVRATTO, J.
700 1 $aFRUGONI, J.C.
700 1 $aMONTOSSI, F.
773 $tln: INIA Tacuarembó. Unidad Experimental Glencoe. Día de Campo Unidad Experimental Glencoe [Colonia Fernando Baccaro, Guarapirú, Paysandú], 2012. Propuestas tecnológicas para sistemas ganaderos de Basalto. Tacuarembó (Uruguay): INIA, 2012.
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INIA Tacuarembó (TBO) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
11/12/2018 |
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Actualizado : |
18/06/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
TONUSSI, R. L.; SILVA, R. M. D. O.; MAGALHÃES, A.F.B.; ESPIGOLAN, R.; PERIPOLLI, E.; OLIVIERI, B. F.; FEITOSA, F. L. B.; LEMOS, M. V. A.; BERTON, M. P.; CHIAIA, H. L. J.; PEREIRA, A. S. C.; LÔBO, R. B.; BEZERRA, L. A. F.; MAGNABOSCO, C. D. U.; LOURENÇO, D.A.L.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
RAFAEL LARA TONUSSI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; RAFAEL MEDEIROS DE OLIVEIRA SILVA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; FABRÍCIA BRAGA MAGALHÃES, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; RAFAEL ESPIGOLAN, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazi; ELISA PERIPOLLI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; BIANCA FERREIRA OLIVIERI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; FABIELI LOISE BRAGA FEITOSA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; MARCOS VINICÍUS ANTUNES LEMOS, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; MARIANA PIATTO BERTON, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; HERMENEGILDO LUCAS JUSTINO CHIAIA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; ANGELICA SIMONE CRAVO PEREIRA, Department of Nutrition and Animal Production, Faculty of Animal Science and Food Engineering, Pirassununga, Brazil; RAYSILDO BARBOSA LÔBO, National Association of Breeders and Researchers (ANCP), Ribeirão Preto, Brazil; LUIZ ANTÔNIO FRAMARTINO BEZERRA, Department of Genetic, Medical School of Ribeirão Preto, Ribeirão Preto, Brazil; CLÁUDIO DE ULHOA MAGNABOSCO, Brazilian Agricultural Research Corporation (EMBRAPA), Distrito Federal, Brazil; DANIELA ANDRESSA LINO LOURENÇO, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, United States of America; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil. |
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Título : |
Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article). |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
PLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS. |
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ISSN : |
1932-6203 |
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DOI : |
10.1371/journal.pone.0181752 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received September 22, 2016 // Accepted July 6, 2017 // Published September 28, 2017.
Data Availability Statement: All relevant data are within the paper, its Supporting Information files, and in Figshare.
Funding: This work was funded by the Sao Paulo Research Foundation (FAPESP), 2013/25910-0, Mr Rafael Lara Tonussi, and Sao Paulo Research Foundation (FAPESP), 2011/21241-0, PhD Fernando Bald. |
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Contenido : |
ABSTRACT.
The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty.
© 2017 Tonussi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. MenosABSTRACT.
The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the popula... Presentar Todo |
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Palabras claves : |
CATTLE; COMPUTER SIMULATION; GENETIC VARIABILITY; GENETICS; GENOMICS; INHERITANCE PATTERNS; PEDIGREE. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12157/1/journal.pone.0181752.pdf
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0181752&type=printable
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181752#sec009
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Marc : |
LEADER 04899naa a2200433 a 4500
001 1059368
005 2019-06-18
008 2017 bl uuuu u00u1 u #d
022 $a1932-6203
024 7 $a10.1371/journal.pone.0181752$2DOI
100 1 $aTONUSSI, R. L.
245 $aApplication of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article).$h[electronic resource]
260 $c2017
500 $aArticle history: Received September 22, 2016 // Accepted July 6, 2017 // Published September 28, 2017. Data Availability Statement: All relevant data are within the paper, its Supporting Information files, and in Figshare. Funding: This work was funded by the Sao Paulo Research Foundation (FAPESP), 2013/25910-0, Mr Rafael Lara Tonussi, and Sao Paulo Research Foundation (FAPESP), 2011/21241-0, PhD Fernando Bald.
520 $aABSTRACT. The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty. © 2017 Tonussi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
653 $aCATTLE
653 $aCOMPUTER SIMULATION
653 $aGENETIC VARIABILITY
653 $aGENETICS
653 $aGENOMICS
653 $aINHERITANCE PATTERNS
653 $aPEDIGREE
700 1 $aSILVA, R. M. D. O.
700 1 $aMAGALHÃES, A.F.B.
700 1 $aESPIGOLAN, R.
700 1 $aPERIPOLLI, E.
700 1 $aOLIVIERI, B. F.
700 1 $aFEITOSA, F. L. B.
700 1 $aLEMOS, M. V. A.
700 1 $aBERTON, M. P.
700 1 $aCHIAIA, H. L. J.
700 1 $aPEREIRA, A. S. C.
700 1 $aLÔBO, R. B.
700 1 $aBEZERRA, L. A. F.
700 1 $aMAGNABOSCO, C. D. U.
700 1 $aLOURENÇO, D.A.L.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tPLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS.
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